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Aladdin-FTI @ AMIYA Three Wishes for Arabic NLP: Fidelity, Diglossia, and Multidialectal Generation

Year: 2026

Type: conference-paper

Abstract: Arabic dialects have long been under represented in Natural Language Processing (NLP) research due to their nonstandardization and high variability, which pose challenges for computational modeling.Recent advances in the field, such as Large Language Models (LLMs), offer promising avenues to address this gap by enabling Arabic to be modeled as a pluricentric language rather than a monolithic system.This paper presents AladdinFTI, our submission to the AMIYA shared task.The proposed system is designed to both generate and translate dialectal Arabic (DA).Specifically, the model supports text generation in Moroccan, Egyptian, Palestinian, Syrian, and Saudi dialects, as well as bidirectional translation between these dialects, Modern Standard Arabic (MSA), and English.The code and trained model are publicly available.1

Source: Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial)

DOI: 10.18653/v1/2026.vardial-1.27

Authors: Jonathan Mutal, Perla Al Almaoui, Simon Hengchen, Pierrette Bouillon

Institution: University of Geneva

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funder: Université de Genève

OpenAlex ID: W7140120147

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